BACKGROUND:Cervical instability is a common orthopedic disease in young and middle-aged people,and is the early manifestation of cervical spondylosis,which has a great impact on the quality of life of patients.Therefore,early diagnosis of cervical instability to implement early intervention has positive clinical and social significance.OBJECTIVE:The clinical prediction model of cervical instability in young and middle-aged people was constructed based on machine learning to realize early screening of cervical instability in young and middle-aged people before X-ray examination.METHODS:From September 2022 to October 2023,155 young and middle-aged adults with cervical instability and 88 with non-cervical instability recruited through recruitment advertisements and spinal department outpatient of Wangjing Hospital,China Academy of Chinese Medical Sciences were selected as research subjects.The research subjects'general information,living and working habits,discomfort symptoms,visual analog scale score,Neck Disability Index,and 36-ltem Short Form Health Survey were collected on site based on questionnaires.The above information was used as predictive factors.After screening,six machine learning algorithms of Support Vector Machine,LightGBM,RandomForest,Logistic,AdaBoost,and XGBClassifier were used to train the model by ten-fold cross-validation method,and the clinical prediction model of cervical instability was constructed.Area under the curve was used as the main evaluation index.Univariate analysis was performed on the predictors,and SHAP method was used to rank the importance of the predictors.Correlation heat maps were used to show the degree of linear correlation between the predictors and the cervical instability.RESULTS AND CONCLUSION:(1)Among the six machine learning models,RandomForest model was chosen as the final prediction model,including nine predictors,such as age,body mass index,neck circumference/neck length,visual analog scale score,Neck Disability Index,bodily pain,general health,vitality,and mental health,area under the curve=0.725 4,and the calibration degree was good.It could be used as a reference tool for early screening of cervical instability in young and middle-aged people.(2)There were significant differences in age,visual analog scale score,Neck Disability Index,bodily pain,general health,and vitality between the two groups(P＜0.05).(3)The order of importance of predictors was age,Neck Disability Index,visual analog scale score,general health,body mass index,vitality,bodily pain,neck circumference/neck length,mental health,among which age,visual analog scale score,Neck Disability Index were positively correlated with cervical instability,while general health,body mass index,vitality,bodily pain,neck circumference/neck length,and mental health were negatively correlated with cervical instability.

Objective:To evaluate physicochemical and immune efficacy of filamentous hemagglutinin(FHA)and pertactin(PRN)before and after detoxification treatment in acellular pertussis vaccine.Methods:Thermal stability of FHA and PRN was analyzed by differential scanning fluorescence(DSF)to evaluate melting temperature(Tm)changes of antigen before and after detoxi-fication treatment.Immune efficacy of vaccine containing single FHA or PRN component and acellular pertussis vaccine with pertussis toxin(PT)was assessed by modified intracerebral challenge assay(MICA)and pertussis serological potency test(PSPT).ELISpot and flow cytometry were utilized to evaluate cytokines secretion and immune cells level in spleens obtained from immunized mice.Results:Under detoxification treatment Tm of FHA changed from a single value 57℃to both 58℃and 81℃,but Tm of PRN were both 84℃.Detoxification treatment had no obvious effects on immune efficacy and IL-4/IFN-γ secretion in spleens from mice.In addi-tion,there was no significant difference in splenic immune cells such as CD4+T,CD8+T and CD44+CD62L+memory cells.Conclu-sion:Detoxification treatment of FHA and PRN have no effect on immune efficacy of acellular pertussis vaccine,except for impact on Tm of FHA.

Triggering receptor expressed on myeloid cells 2 （TREM2） is expressed in resident non-parenchymal cells （NPCs） and is involved in various pathological processes including liver inflammation and immunoregulation. In recent years， TREM2 has attracted attention in the field of acute and chronic liver diseases， and more and more studies have shown that TREM2 is a potential target for the treatment of acute and chronic liver diseases； however， there is a lack of systematic summary for the mechanism of action of TREM2 in acute and chronic liver diseases. Therefore， this article reviews the latest research advances in the regulatory role of TREM2 in acute and chronic liver diseases， in order to provide new ideas for the clinical prevention and treatment of acute and chronic liver diseases.

Autoimmune hepatitis （AIH） is an autoimmune disease characterized by liver parenchymal destruction and chronic fibrosis， and it is often mediated by T cells. The pathogenesis of AIH involves multiple factors， including sex， region， environmental factors， and genetic susceptibility. A notable predisposition is observed in female individuals， and the incidence rate of AIH in female individuals is significantly higher than that in male individuals. This sex difference is associated with various factors， and sex hormones may be an important cause of the female predominance of AIH， although the specific mechanisms remain unclear. An in-depth understanding of the mechanism of action of sex hormones in the pathogenesis of AIH will help to better understand the pathogenesis of the disease and may provide important clues for developing future treatment methods and prevention strategies. This article reviews the mechanism of action of estrogen and androgen in regulating the pathogenesis of AIH by regulating T cells， in order to provide new ideas and directions for further exploring the potential role of sex hormones in the etiology of autoimmune diseases.

This study aims to investigate the relationship between serum vitamin A(VA)and mar-bling grade and the effect of different levels of serum VA on slaughter performance and fatty acid composition and related gene expression in the longissimus dorsi muscle of Woking black cattle and Angus cattle.Thirty Woking black cattle and seventeen Angus cattle aged 30 months were ran-domly selected and analyzed for the linear relationship between serum VA and marbling grade af-ter slaughter.The cattle were divided into three groups:the low VA group,medium VA group and high VA group,ranked in order of VA value in both Woking black cattle and Angus cattle.Statisti-cal analysis of the effects of different types and levels of VA on marbling grade,slaughter performance,fatty acid composition,and the effects of different levels of VA on the expression of genes related to intramuscular fat deposition and other genes in Woking black cattle or Angus cat-tle were also analyzed.The results showed that the marbling grade of Woking black cattle increased numerically with increasing serum VA at slaughter(P=0.203),whereas Angus cattle showed a numerical decrease(P=0.139).Analyses of subsequent subgroups showed that Woking black cat-tle had significantly higher marbling grade and oleic acid,monounsaturated/saturated fatty acids ratio in the longissimus dorsi muscle compared to Angus cattle(P＜0.05).As serum VA levels in-creased,DHA was significantly higher and n-6/n-3 fatty acid ratio significantly lower in the longis-simus dorsi muscle of Woking black cattle(P＜0.05).Whereas VA was elevated in Angus cattle,a significant decrease in DHA and a significant increase in n-6/n-3 fatty acids(P＜0.05)were found.Furthermore,a notable up-or down-regulation(P＜0.05)of LPL,FABP4,PPARγ,C APZA2 and Villin 2 was observed in Woking black or Angus cattle,respectively,as VA levels increased.Based on these results,it was suggested that Woking black cattle require an appropriate increase in dieta-ry VA during the late fattening stage,which was found to produce a higher marbling grade and a higher percentage of beneficial fatty acids for human health when serum VA reached 80.7 IU/dL.Whereas Angus cattle still need to be restricted in ration VA content in the late fattening stage,when serum VA is elevated to 73.6 IU/dL,they produce beef that not only has a lower marbling grade but also has a corresponding reduction in fatty acids beneficial to human health.

This study aims to investigate the relationship between serum vitamin A(VA)and mar-bling grade and the effect of different levels of serum VA on slaughter performance and fatty acid composition and related gene expression in the longissimus dorsi muscle of Woking black cattle and Angus cattle.Thirty Woking black cattle and seventeen Angus cattle aged 30 months were ran-domly selected and analyzed for the linear relationship between serum VA and marbling grade af-ter slaughter.The cattle were divided into three groups:the low VA group,medium VA group and high VA group,ranked in order of VA value in both Woking black cattle and Angus cattle.Statisti-cal analysis of the effects of different types and levels of VA on marbling grade,slaughter performance,fatty acid composition,and the effects of different levels of VA on the expression of genes related to intramuscular fat deposition and other genes in Woking black cattle or Angus cat-tle were also analyzed.The results showed that the marbling grade of Woking black cattle increased numerically with increasing serum VA at slaughter(P=0.203),whereas Angus cattle showed a numerical decrease(P=0.139).Analyses of subsequent subgroups showed that Woking black cat-tle had significantly higher marbling grade and oleic acid,monounsaturated/saturated fatty acids ratio in the longissimus dorsi muscle compared to Angus cattle(P＜0.05).As serum VA levels in-creased,DHA was significantly higher and n-6/n-3 fatty acid ratio significantly lower in the longis-simus dorsi muscle of Woking black cattle(P＜0.05).Whereas VA was elevated in Angus cattle,a significant decrease in DHA and a significant increase in n-6/n-3 fatty acids(P＜0.05)were found.Furthermore,a notable up-or down-regulation(P＜0.05)of LPL,FABP4,PPARγ,C APZA2 and Villin 2 was observed in Woking black or Angus cattle,respectively,as VA levels increased.Based on these results,it was suggested that Woking black cattle require an appropriate increase in dieta-ry VA during the late fattening stage,which was found to produce a higher marbling grade and a higher percentage of beneficial fatty acids for human health when serum VA reached 80.7 IU/dL.Whereas Angus cattle still need to be restricted in ration VA content in the late fattening stage,when serum VA is elevated to 73.6 IU/dL,they produce beef that not only has a lower marbling grade but also has a corresponding reduction in fatty acids beneficial to human health.

Alzheimer's disease (AD) remains a formidable challenge in modern healthcare, necessitating innovative approaches for its early detection and intervention. This study aimed to enhance the identification of individuals with mild cognitive impairment (MCI) at risk of developing AD. Leveraging advances in computational power and the extensive availability of healthcare data, we explored the potential of deep learning models for early prediction using medical claims data. We employed a bidirectional gated recurrent unit (BiGRU) deep learning model for predictive modeling of MCI progression across various prediction intervals, extending up to five years post-initial MCI diagnosis. The performance of the BiGRU model was rigorously compared with several machine-learning model baselines to evaluate its efficacy. Using a robust cross-validation methodology, the BiGRU emerged as the top-performing model, achieving an Area Under the Receiver Operating Characteristic Curve (AUC-ROC) of 0.833 (95% CI: 0.822, 0.843), an Area Under the Precision-Recall Curve (AUC-PR) of 0.856 (95% CI: 0.845, 0.867), and an F1-Score of 0.71 (95% CI: 0.694, 0.724) for a five-year prediction interval. The results indicate that BiGRU, utilizing longitudinal claims data, reliably predicts MCI-to-AD progression over a lengthy interval following the initial MCI diagnosis, offering clinicians a valuable tool for targeted risk identification and stratification.

Asthma is one of the most common diseases in chronic respiratory system;the etiology is complex,in-volving many types of inflammatory cells and a variety of signaling molecular mediators.Hydrogen sulfide(H2 S)is an endogenous gas transmitter in mammals,which is widely involved in cell functions and physiological and pathological processes of various diseases,including respiratory diseases.H2 S is involved in the occurrence and development of asthma through various ways.When the H2 S-producing enzyme level decreases,the concentration of endogenous H2 S level may trigger asthma attack and play a pro-inflammatory role.On the other hand,H2 S ini-tiates pulmonary inducible nitric oxide synthase(iNOS)activation,limiting airway remodeling,and acts as an anti-remodeling and anti-inflammatory mediator.Moreover,H2 S level varies at different stages of asthma.H2 S level in patients with asthma is a potential bio-markers of airway inflammation in asthma case and my support clin-ical diagnosis of asthma.

BACKGROUND:Cervical instability is a common orthopedic disease in young and middle-aged people,and is the early manifestation of cervical spondylosis,which has a great impact on the quality of life of patients.Therefore,early diagnosis of cervical instability to implement early intervention has positive clinical and social significance.OBJECTIVE:The clinical prediction model of cervical instability in young and middle-aged people was constructed based on machine learning to realize early screening of cervical instability in young and middle-aged people before X-ray examination.METHODS:From September 2022 to October 2023,155 young and middle-aged adults with cervical instability and 88 with non-cervical instability recruited through recruitment advertisements and spinal department outpatient of Wangjing Hospital,China Academy of Chinese Medical Sciences were selected as research subjects.The research subjects'general information,living and working habits,discomfort symptoms,visual analog scale score,Neck Disability Index,and 36-ltem Short Form Health Survey were collected on site based on questionnaires.The above information was used as predictive factors.After screening,six machine learning algorithms of Support Vector Machine,LightGBM,RandomForest,Logistic,AdaBoost,and XGBClassifier were used to train the model by ten-fold cross-validation method,and the clinical prediction model of cervical instability was constructed.Area under the curve was used as the main evaluation index.Univariate analysis was performed on the predictors,and SHAP method was used to rank the importance of the predictors.Correlation heat maps were used to show the degree of linear correlation between the predictors and the cervical instability.RESULTS AND CONCLUSION:(1)Among the six machine learning models,RandomForest model was chosen as the final prediction model,including nine predictors,such as age,body mass index,neck circumference/neck length,visual analog scale score,Neck Disability Index,bodily pain,general health,vitality,and mental health,area under the curve=0.725 4,and the calibration degree was good.It could be used as a reference tool for early screening of cervical instability in young and middle-aged people.(2)There were significant differences in age,visual analog scale score,Neck Disability Index,bodily pain,general health,and vitality between the two groups(P＜0.05).(3)The order of importance of predictors was age,Neck Disability Index,visual analog scale score,general health,body mass index,vitality,bodily pain,neck circumference/neck length,mental health,among which age,visual analog scale score,Neck Disability Index were positively correlated with cervical instability,while general health,body mass index,vitality,bodily pain,neck circumference/neck length,and mental health were negatively correlated with cervical instability.

Objective:To evaluate the clinical utility of dual-layer detector CT integrated with virtual monoenergetic imaging (VMI) and an orthopedic metal artifact reduction (O-MAR) algorithm in improving the image quality of patients after lumbar pedicle screw fixation surgery, and to analyze its impact on different types of artifacts and image quality of different tissues.Methods:The study was a prospective study, The study enrolled patients who underwent lumbar pedicle screw fixation at West China Hospital of Sichuan University between March and September 2024. All patients underwent lumbar CT scans using a dual-layer detector system, and four image sets were reconstructed. CLumbar routine scans were performed using dual-layer detector CT, and four image sets were reconstructed:onventional images (CI non-O-MAR), conventional images with O-MAR (CI O-MAR), virtual monoenergetic images (VMI non-O-MAR), and VMI with O-MAR (VMI O-MAR). Objective metrics including artifact index (AI), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were quantified, alongside subjective image quality assessment. One-way ANOVA or Friedman test were used to compare the objective evaluation indicators of image quality between VMI non-O-MAR and VMI O-MAR at different energy levels. Paired t-test or Wilcoxon signed-rank test was used for CI non-O-MAR/VMI non-O-MAR versus CI O-MAR/VMI O-MAR comparisons. Results:A total of 30 patients were included, and all underwent internal fixation with titanium alloy pedicle screws. Objective analysis revealed that in both high-and low-density artifact regions, the AI values of the VMI O-MAR group decreased with the increase of energy levels, and were significantly lower than those of the corresponding VMI non-O-MAR group, with a statistically significant difference (all P<0.001). When the energy level≥140 keV, the AI value of the VMI O-MAR group was simultaneously lower than that of the CI non-O-MAR group and the CI O-MAR group, with statistically significant differences (all P<0.05). The SNR and CNR on the vertebral bodies in the VMI non-O-MAR group and the VMI O-MAR group showed a decreasing trend with increasing energy levels, and were always lower than those in the CI group at high energy levels (100-180 keV) (all P<0.05). At high energy levels (100-180 keV), the SNR of VMI O-MAR in the intervertebral disc and intraspinal tissues was higher than that of the VMI non-O-MAR group, with statistically significant differences (all P<0.05). Compared to other groups, subjective analysis indicated that the 140 keV VMI combined with O-MAR group received the highest image quality scores ( P<0.05). Conclusions:The combined application of VMI and O-MAR technology effectively reduces metal artifacts in post-lumbar fixation CT images. The 140 keV VMI with O-MAR reconstruction provides superior image quality and enhances diagnostic confidence.